I think a big part of why this happens is that a lot of the fundamental math of CAD doesn't have good answers - everything is heuristics and approximations to within a tolerance.
You can get a simple NURBS kernel up and running in maybe 2 dev-years. But getting good heuristics created for all of the common edge cases is what takes the huge number of dev-decades, and what you pay for with one of the commercial kernels. You won't even know what the common edge-cases are until you start getting user reports of things failing, so you'll need to be doing this development with a large community of users.
There is no closed-form formula to tell how long a NURBS curve is. Offsets of NURBS curves are not NURBS curves. Likewise, intersecting NURBS surfaces produces intersection curves that are not possible to represent as NURBS curves.
So something as simple as a fillet is impossible to exactly produce in like 3 ways. Booleans then add the joy of topology to the mix. It's all heuristics and approximations and dirty hacks.
While this is true of programs like Rhino, it's not as true for fusion360. There are no NURBS in fusion360.
I would guess that the fusion360 kernel is very focussed on deterministic solutions, specially being constraint based, where the errors in heuristics would multiply across the history. Interestingly, in situations where the math has more guesswork, as I think lofts and such are, fusion can be really quite bad.
Rhino is amazingly good (and it's many many years old).
Fusion360 is just a baby but it's pretty good for what it does. Once you use constraints based CAD it's hard to go back.
While Fusion 360 does have many non-NURBS procedural surfaces, they definitely also have NURBS. Otherwise you wouldn't be able to import an IGES or step file.
Using a solids kernel with procedural surfaces can help many cases, as you keep the modeling tree around and can recompute portions at higher tolerance as needed. However that's just another cumbersome workaround to the fundamental problem that the math doesn't have clean solutions.
I'd heard people say that the architecture of a city is usually frozen in the time when it had the most money.
If you look at the skyscrapers and other buildings from Zaha Hadid, they're not Art Deco. UAE and other countries which are currently building out significantly aren't sticking just to Art Deco. London is interesting in that they've had money pouring in for a long time, and have an eclectic mix of large buildings.
Right, like the example from Target. It is possible that facebook has access to a stream of Target purchases or credit card purchase information. I'd be 0% surprised if there was a data sharing agreement with credit rating companies.
Even if they just knew the price of the purchase, combined with the job (burn risk) and location data (traveled from work to nearest store with pharmacy during the day), it's possible that you might be able to infer a burn with enough accuracy to be valuable to advertisers.
"It is possible that facebook has access to a stream of Target purchases" ...
It's not possible, it's simply true. In fact, this feature of the facebook ad platform is available to any advertiser on Facebook/Instagram/etc, whether you have $100 to spend or $100M.
You simply upload your customer's purchases to Facebook with data such as zip code, email, etc etc which Facebook then uses to optimize your advertising budget and find more customers similar to the ones you already have (the feature is called look-alike audiences).
I'm sure Facebook would like to do what you're saying, but I think that they're a long way from having those capabilities.
They have billions of users, billions of ads, and trillions of pieces of metadata. Sifting through that to produce a guess like "User 1234 burned themselves and would be interested in product 5678" would be an amazing and scary piece of AI.
Not to mention that Facebook are limited by the ads they can sell. The manufacturer of the burn cream doesn't give Facebook a bucket of money and free reign. They choose how and where the ads are shown. There is currently no option for "Users who recently burned themselves".
Last year there were 29,000 categories that could be targeted. If an ad sales rep wanted to close a deal, how difficult would it be to add one more for recent burn victims, or people who recently bought a specific product?
From the links that m_ke posted, facebook already has ties to loyalty card information, so it's very possible that they didn't need to do any inference, they just had the data directly.
In any case, the main point is that facebook doesn't need to listen to what people are saying, it has a ton of other data streams that could explain the stories in the link.
What would the point be in advertising a burn cream to someone that just bought a burn cream? It's not like it's a common reoccurring purchase (like Toothpaste for example).
Like the article says, it's probably just the Baader-Meinhof phenomenon* at work. It's like when you buy a new car - you suddenly start seeing that same model of car everywhere.
I think the proposed logic here is "a person like you buys burn cream so we advertise burn cream to people like you." In this scenario the person who actually bought the item will get the ad too.
To me, advertising a product to people who already bought it is a sound strategy. I see no contradiction. I'd rather like to hear a cogent argument as to why that is wasted effort, as is usually implied.
In your example, maybe I left the bottle of burn cream at the office. So I will want to get another one on the way home. It's effective to get reminded in my Facebook about that item (and the brand) isn't it? Yes it's creepy but it works.
> facebook doesn't need to listen to what people are saying, it has a ton of other data streams
The same could be said for any of those data streams. But just because Big F has access to those other sources of data doesn't mean it excludes voice recognition.
I'd be very surprised if FB wasn't in this arena. That's how big tech companies work these days — they do what everyone else is doing. Like getting into self-driving cars.
Apple[1], Google, Amazon, MS, etc... all have voice recognition boxes. FB doesn't need to market a box for your living room, it already has one in everyone's pocket.
([1] Apple says it doesn't use any of your Siri words against you. If you don't trust FB's word, you might no trust Apple's, either. But at least on the Mac you can keep dictation off the internet, if you choose.)
I agree that even with an enormous amount of data there are limits to what facebook can realistically infer...I particularly enjoyed the things that facebook’s ad platform determined to be my hobbies when I checked recently: https://m.imgur.com/nWCWn63
I’ve had an account since 2005, even if I use it much less than I used to, you’d think they’d have enough data to do better than that.
Think smaller. They don't need to consider billion users at once, for modeling you can start with hundreds of thousands or few million. Trillion pieces of metadata can be reduced to tens of thousands of features (eg. instead of feeding in the raw status updates, assign each update to some class, put in some mood measurement etc). This reduction does not need to be fully automated, it can be human assisted (humans coming up with ideas on what kind of features to extract). Instead of considering all possible ads, you can start by taking out the long tail of ads with very little interaction data and focus on some specific categories.
Building this kind of predictive models is not black magic. This is what companies do to figure out who they should target on direct marketing campaigns. Applying some magical deep learning dust can quite likely improve the results (in Facebook scale), but it's not mandatory. Computationally the hardest part is building the models. Once they are done, applying them to millions and millions of customers is more straight forward.
When considering what is possible, you need to also consider the stakes. Facebook ad revenue is something like $10 billion per quarter[1]. To make more money, I can think of three ways: add more users, make users spend more time looking at their feed or make more money per ad slot. Better targeting means more money per ad slot since some customers are paying directly based on the clicks. Since improvements lead to better revenue, extra hardware costs are easy to justify.
Also, Googling something on your phone is so common and easy nowadays that people just forget that they did it. It's literally become an integral part of the thinking process.
Rewards cards / loyalty card are designed to incentivize you to spend more with the stores. Ostensibly reselling data is a lot less valuable than directly trying to convince you to shop more at their establishments
That was true at the beginning of the loyalty card phage. But now the big chains are learning how to data mine and discovering the value of their data to others.
Now your loyalty card data is worth twice as much. Once to the retailer for internal marketing, targeting, purchasing, etc... and again selling it to outside parties.
thanks, sorry to reply to this late. I often wonder if I take a loyalty card and then for example I purchase twice as much double cream as the next person, does this get sold to health insurers who then charge me a higher premium? The permutations are endless eg too much beer. too many condoms. Too much spicy dip.
If you look at the history of the Tesco Clubcard (one of the early ones to appear in the UK), the data they mined from their new ability to tie purchasing trends to customers more than made up for the cost of the rewards being offered to get people to use it.
There's a reason they got so dominant over here - they were simply way ahead of the game on offering what their customers actually wanted, because they were the only people who actually had a clue.
If you read the Walgreens Rewards privacy policy, it covers everything from retail transactions to security camera footage and they are able to tie everything together. They're also able to gather and sell data about your health, which would otherwise be protected by regulation using the rewards program, especially as people are incentivized to use the card, even for prescriptions...and no one actually reads [between the lines] of the privacy policy
That's true and credit card companies are very open about it (at least if you read their reports for investors). The advantage of store cards is that the store knows exactly which products you bought, whereas they only know the total if you used a Mastercard/Visa.
>whereas they only know the total if you used a Mastercard/Visa
This is simply not true with respect to the big retailers in the US. This started as far back as '06, though the details of the implementation have changed a bit.
Only if it's a co-branded card. If you use your Visa issued by some bank to go shopping at Walmart, they won't get your personal details together with all items you bought. They can get the items but without the personal details (including age, wealth, etc), they're not that useful.
We had the ability to do this at the largest merchant acquirer 10 years ago as long as your bank signed up. Walmart was one of the first customers and would stream SKU-level data straight to our servers from the POS terminal.
Facebook is amassing a huge amount of valuable information on every member.
I disagree that the threat of outrage is sufficient to stop the information being used badly. For example, there is outrage against Equifax, but their cache of information has still been compromised. We have seen data leak after data leak from various companies. If a country's spy agencies want to go after the data, they have a lot of resources, from hacking to legislation to physical intrusion or coercion.
Add to that, it seems like Facebook doesn't institutionally care about privacy (probably because it is hard to explain something to someone whose paycheck depends on them not understanding it). For example, http://actualfacebookgraphsearches.tumblr.com has some very damaging graph searches. Or people who have been outed as gay by incomprehensible privacy settings.
Facebook is a sieve, and the reason to care about them having a lot of information is the same reason to care about privacy in general.
Remember when Target snitched to a teenager’s parents that she was pregnant because her purchases fit the “is pregnant” profile, and everyone got outraged, and they stopped profiling people?
Actually, only one of those things happened, the one in the middle. I'll let you dig into Forbes's "sources" to figure out how they managed to twist a hypothetical into something that already happened.
The author talked to an employee who talked to the man whose daughter was flagged as pregnant. It would be nice if they could have talked directly to the man, but that doesn't seem too distant. In any case, it hardly seems to warrant a scare-quoted "sources," nor would I describe that as "twist a hypothetical."
You have now refuted the story twice in this thread without providing any evidence of its inaccuracies. While I don’t know for certain the validity of the story, you aren’t doing much to persuade me of your position.
I ... don’t know what to say. What they are doing now is respectful?
If we ever come to widespread outrage, it will be much to late. In fact, I don’t think there can be outrage. FB would detect it and make it disappear. Somehow.
In the UK, some Amazon deliveries were sent via 'Amazon Logistics', which was usually someone in a little car full of packages. I think it's been going on for at least the last 3 or 4 years?
They've had the same in the US for a while as well. What makes this different is that they are handling both sides of the delivery, whereas before they were delivering from their own warehouse.
we should note, there are multiple types of dyslexia, each are very different. I am pretty darn dyslexic, and the dyslexic fonts don't help me at all, in fact they make it harder to read. But my issue wasn't really with reading, I have more problems writing.
Another issue of letting sellers glom on to the main product SKU listing is that the reviews are all over the map, and there's no way for a customer to tell which review came from which seller.
I bought some tripod mounts for a VR rig - some of the reviews said they were plastic, some said metal, some said the quality was good or bad, etc. I rolled the dice, and got metal ones that smelled so badly of gasoline that I couldn't keep them in the house. Ended up buying some name brand, that at least had predictable quality.
There are lots of things that Amazon could do to counter these issues. Just look at what they are doing for Prime and 'sold by Amazon' - there is a big checkbox when searching to only show prime-eligible items, and when looking at the list of sellers, amazon is shown prominently with different graphics. They could easily do the same things for verified owners of products, so that OEMs could sell on Amazon and customers could be sure they're buying a genuine article.
If it were truly an insoluble problem, why are there no 'Amazon Basics' counterfeits on the market?
The first impact of self-driving cars will be much worse traffic. While ride-sharing and public transit are helpful, they are nowhere near as good as self-driving cars.
If you had a self-driving car you'd be able to set up a truly productive or relaxing environment, which you're unable to fully replicate on public transit. For example, stick in a mattress with your favorite pillow, add a shower, have a desk with nice big monitors, a webcam to take video calls, etc. Aside from just being transportation, a car is also a bubble of quiet, cleanliness, and personal security. It is a mini house on wheels, a portable locker, and a refuge.
And since you're not driving, who cares about the traffic?
Eh I can't find citations right now because I am trying to be productive but modellers and people who study this argue that a lot of traffic is caused by sub-optimal driver behavior. Specifically issues with merging/ and phantom waves that build up and cause phantom jams. Accordingly people think the self driving cars will not be susceptible to this -> less traffic(?). I do not know I agree with these claims since I haven't looked at the math but I am not so sure self driving cars will lead to "much worse" traffic than human driven cars.
MP3 is more widely supported than any lossless audio codec. Lossless compression enables the collector to keep an original.
Not everyone is a collector though - for them, MP3 is probably fine, and if they need a different format later they'll probably just stream, re-encode, or re-purchase, in order of likelihood.
You can get a simple NURBS kernel up and running in maybe 2 dev-years. But getting good heuristics created for all of the common edge cases is what takes the huge number of dev-decades, and what you pay for with one of the commercial kernels. You won't even know what the common edge-cases are until you start getting user reports of things failing, so you'll need to be doing this development with a large community of users.
There is no closed-form formula to tell how long a NURBS curve is. Offsets of NURBS curves are not NURBS curves. Likewise, intersecting NURBS surfaces produces intersection curves that are not possible to represent as NURBS curves.
So something as simple as a fillet is impossible to exactly produce in like 3 ways. Booleans then add the joy of topology to the mix. It's all heuristics and approximations and dirty hacks.